Triple
T20120739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fun in Acapulco |
E490598
|
entity |
| Predicate | leadCharacterPastOccupation |
P35945
|
FINISHED |
| Object | trapeze artist |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: trapeze artist | Statement: [Fun in Acapulco, leadCharacterPastOccupation, trapeze artist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterPastOccupation Context triple: [Fun in Acapulco, leadCharacterPastOccupation, trapeze artist]
-
A.
characterFormerOccupation
chosen
Indicates that a character previously held a specific occupation but no longer does.
-
B.
economicRolePast
Indicates that an entity previously held a specific economic function, position, or role in the past.
-
C.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
D.
hasPastOccupation
Indicates that an entity previously held a particular job, role, or occupation in the past.
-
E.
namedAfterOccupationOrRole
Indicates that an entity is named after a specific occupation, profession, or social role associated with a person or group.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6673e79dc81908fbd387c067fce79 |
completed | April 20, 2026, 5:49 p.m. |
| PD | Predicate disambiguation | batch_69e54cf788188190a46cc49c9ce7617f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:30 p.m.